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Modeling the effector - regulatory T cell cross-regulation reveals the intrinsic character of relapses in Multiple Sclerosis

机译:建模效应物-调节性T细胞交叉调节揭示多发性硬化症复发的内在特征

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Background The relapsing-remitting dynamics is a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). Although current understanding of both cellular and molecular mechanisms involved in the pathogenesis of autoimmune diseases is significant, how their activity generates this prototypical dynamics is not understood yet. In order to gain insight about the mechanisms that drive these relapsing-remitting dynamics, we developed a computational model using such biological knowledge. We hypothesized that the relapsing dynamics in autoimmunity can arise through the failure in the mechanisms controlling cross-regulation between regulatory and effector T cells with the interplay of stochastic events (e.g. failure in central tolerance, activation by pathogens) that are able to trigger the immune system. Results The model represents five concepts: central tolerance (T-cell generation by the thymus), T-cell activation, T-cell memory, cross-regulation (negative feedback) between regulatory and effector T-cells and tissue damage. We enriched the model with reversible and irreversible tissue damage, which aims to provide a comprehensible link between autoimmune activity and clinical relapses and active lesions in the magnetic resonances studies in patients with Multiple Sclerosis. Our analysis shows that the weakness in this negative feedback between effector and regulatory T-cells, allows the immune system to generate the characteristic relapsing-remitting dynamics of autoimmune diseases, without the need of additional environmental triggers. The simulations show that the timing at which relapses appear is highly unpredictable. We also introduced targeted perturbations into the model that mimicked immunotherapies that modulate effector and regulatory populations. The effects of such therapies happened to be highly dependent on the timing and/or dose, and on the underlying dynamic of the immune system. Conclusion The relapsing dynamic in MS derives from the emergent properties of the immune system operating in a pathological state, a fact that has implications for predicting disease course and developing new therapies for MS.
机译:背景复发缓解动力学是自身免疫性疾病(例如多发性硬化症(MS))的标志。尽管目前对自身免疫性疾病发病机理中涉及的细胞和分子机制的理解十分重要,但尚不清楚它们的活性如何产生这种原型动力学。为了深入了解驱动这些复发缓解动力学的机制,我们使用此类生物学知识开发了一个计算模型。我们假设自身免疫的复发动力可能是由于控制T细胞和效应T细胞之间交叉调控的机制失败,以及随机事件(例如中枢耐受性失败,病原体激活)相互作用而触发的,从而触发免疫反应。系统。结果该模型代表五个概念:中枢耐受性(胸腺生成T细胞),T细胞活化,T细胞记忆,调节性T细胞和效应T细胞之间的交叉调节(负反馈)以及组织损伤。我们用可逆性和不可逆性组织损伤丰富了该模型,旨在在多发性硬化症患者的磁共振研究中提供自身免疫活性与临床复发和活动性病变之间的可理解联系。我们的分析表明,效应器和调节性T细胞之间这种负反馈的弱点使免疫系统无需额外的环境触发因素即可产生自身免疫性疾病的特征性复发-释放动力学。模拟表明,出现复发的时间是高度不可预测的。我们还向模型中引入了目标扰动,该模型模仿了调节效应子和调节群体的免疫疗法。这种疗法的效果恰好高度依赖于时间和/或剂量,以及免疫系统的内在动力。结论MS的复发动态源于在病理状态下运行的免疫系统的新特性,这一事实对预测MS的病程和开发新疗法具有重要意义。

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